After founding and building an AI company in the climate finance space, Pioneer—where we helped our clients win over $175 million in government grants and tax credits in less than 18 months—one thing became clear: AI alone isn’t enough. In many specialized industries, human expertise still plays a critical role. But the upside for startups that combine AI with specialized human know-how is massive—even in “niche” markets that VCs have historically written off as too small.

AI still needs human expertise
Although AI has advanced quickly, it can’t (yet) replace human insight in many high-stakes or highly specialized workflows. Clients care about outcomes and trust; if the result is mission-critical or financially significant, they want accountability from people, not just machines. Net promoter score (NPS), retention, and account expansion hinges on having experienced experts who can guide, interpret, and validate AI-driven work. That personal relationship and trust factor makes all the difference.

Why old TAM math no longer applies
Traditionally, software solutions in niche verticals suffered from low average contract values (ACVs). You might sell a $10,000-per-year tool to automate part of a workflow. But in the AI era, the game changes:

• Tapping Headcount Budgets: Instead of selling a tool that supports existing teams, AI startups can outright replace or augment entire roles. That means you can price your solution in line with what a customer would otherwise spend on headcount—tens or hundreds of thousands of dollars per year.​

• 10x–100x ACVs: The difference between a $10k software license and a $100k–$1M “AI + expert” service is transformative. A niche market with only 10,000 potential customers can suddenly support a TAM leap from $100M to low billions, based solely on bigger ACVs.

TAM expansion through a better experience
Beyond higher ACVs, smarter AI + human solutions can expand the total market itself. Think about Uber’s impact on the taxi industry: by improving convenience, speed, and cost, Uber unlocked a wave of new users who rarely took cabs before. Similarly, an AI-powered service that reduces complexity or cost can attract brand-new customers who previously didn’t see enough value in the legacy approach.

Why this moment is special

This is an amazing time to build an AI startup. Many industries that were previously considered too “small TAM” for venture investment are now wide open. These customers aren’t living under a rock—they see what’s happening in AI, and many are eager early adopters. That creates an opportunity to move fast before others catch on.

 

How to win quickly

1. Focus on niche verticals that were previously overlooked by software founders and investors due to small TAM.

2. Take on headcount scope—replace work, not just assist it, and charge accordingly. But be sure to start narrow, then expand methodically over time.

3. Increase the distribution of work the AI does over time, maintaining human oversight and client relationships to ensure quality and build trust.

4. Look beyond today’s market size—think about how AI can expand the market the way Uber did for ride-sharing.

Now is the time
We’re at a moment when vertical AI startups can redefine what “market size” really means. By combining highly efficient AI with the human quality and trust factors—and by charging in line with headcount budgets—you can multiply ACVs, expand market scope, and deliver solutions that feel revolutionary to historically underserved customers. Don’t overlook niche industries: the TAM is bigger than you think, and the window to build a category-defining AI company in these spaces has never been wider.

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This thesis is still being tested in real time. If you’re a founder, investor, or engineer exploring AI in overlooked industries, reach out at kyle.treige@gmail.com—I’d love to learn from what you’re seeing.